Simulating Reactive Motions for Motion Capture Animation

  • Bing Tang
  • Zhigeng Pan
  • Le Zheng
  • Mingmin Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4035)


In this paper, we propose a new method for simulating reactive motions for motion capture animation. The goal is to generate realistic behaviors under unexpected external forces. A set of techniques are introduced to select a motion capture sequence which follows an impact, and then synthesize a believable transition to this found clip for character interaction. Utilizing a parallel simulation, our method is able to predict a character’s motion trajectory under dynamics, which ensures that the character moves towards the target sequence and makes the character’s behavior more life-like. In addition, the mechanism of parallel simulation with different time steps is flexible for simulation of multiple contacts in a series when multiple searches are necessary. Our controller is designed to generate physically plausible motion following an upcoming motion with adjustment from biomechanics rules, which is a key to avoid an unconscious look for a character during the transition.


Motion Capture Protective Behavior Simulated Motion Physical Simulation Parallel Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Lee, J., Shin, S.Y.: A hierarchical approach to interactive motion editing for humanlike figures. In: The 26th Annual Conference on Computer Graphics and Interactive Techniques, pp. 39–48 (1999)Google Scholar
  2. 2.
    Witkin, A., Popovic, Z.: Motion warping. In: The 22nd Annual Conference on Computer Graphics and Interactive Techniques, pp. 105–108 (1995)Google Scholar
  3. 3.
    Gleicher, M.: Comparing constraint-based motion editing methods. Graphical models 63, 107–134 (2001)MATHCrossRefGoogle Scholar
  4. 4.
    Park, S.I., Shin, H.J., Shin, S.Y.: On-line locomotion generation based on motion blending. In: The 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation, pp. 105–111. ACM Press, New York (2002)CrossRefGoogle Scholar
  5. 5.
    Kovar, L., Gleicher, M., Pighin, F.e.e.: Motion graphs. ACM Transactions on Graphics 21, 473–482 (2002)CrossRefGoogle Scholar
  6. 6.
    Hodgins, J.K., et al.: Animating human athletics. ACM Computer Graphics, 71–78 (1995)Google Scholar
  7. 7.
    Wooten, W.L.: Simulation of Leaping, Tumbling, Landing, and Balancing Humans. Doctoral thesis. Georgia Institute of Technology (1998)Google Scholar
  8. 8.
    Faloutsos, P., van der Panne, M., Terzopoulos, D.: Composable controllers for physics-based character animation. In: ACM SIGGRAPH 2001, pp. 251–260. ACM Press, New York (2001)Google Scholar
  9. 9.
    Oshita, M., Makinouchi, A.: A dynamic motion control technique for human-like articulated figures. In: Eurographics 2001, pp. 192–202 (2001)Google Scholar
  10. 10.
    Shapiro, A., Pighin, F.: Hybrid control for interactive character animation. In: The 11th Pacific Conference on Computer Graphics and Applications, pp. 455–461 (2003)Google Scholar
  11. 11.
    Mandel, M.: Versatile and interactive virtual humans: Hybrid use of data-driven and dynamics-based motion synthesis. Master’s thesis. Carnegie Mellon University (2004)Google Scholar
  12. 12.
    Zordan, V.B., et al.: Dynamic response for motion capture animation. In: ACM SIGGRAPH 2005, pp. 697–701. ACM Press, New York (2005)CrossRefGoogle Scholar
  13. 13.
    Liu, C.K., Hertzmann, A., Popovíc, Z.: Learning Physics-Based Motion Style with Nonlinear Inverse Optimization. ACM Transactions on Graphics 24, 1071–1081 (2005)CrossRefGoogle Scholar
  14. 14.
    Hsiao, E.T., Robinovitch, S.N.: Biomechanical influences on balance recovery by stepping. Journal of Biomechanics 32, 1099–1106 (1999)CrossRefGoogle Scholar
  15. 15.
    Rogers, M.W., et al.: Triggering of protective stepping for the control of human balance: age and contextual dependence. Congitive Brain Research 16, 192–198 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bing Tang
    • 1
  • Zhigeng Pan
    • 1
  • Le Zheng
    • 1
  • Mingmin Zhang
    • 1
  1. 1.State Key Lab of CAD&CGZhejiang UniversityHang ZhouChina

Personalised recommendations